activity
20182023
most citedLow-Light Image Enhancement with Normalizing Flow

33 citations · 76 across the 15 of their papers we have counts for

collaborators
Showing cs.CVShow all

20 papers · 1 filter

cs.CV20231 cited

Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method

Tianyi Liu, Kejun Wu, Yi Wang +3

The past decade has witnessed great strides in video recovery by specialist technologies, like video inpainting, completion, and error concealment. However, they typically simulate…

cs.CV20233 cited

ExposureDiffusion: Learning to Expose for Low-light Image Enhancement

Yufei Wang, Yi Yu, Wenhan Yang +4

Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed…

cs.CV2023

Beyond Learned Metadata-based Raw Image Reconstruction

Yufei Wang, Yi Yu, Wenhan Yang +4

While raw images have distinct advantages over sRGB images, e.g., linearity and fine-grained quantization levels, they are not widely adopted by general users due to their substant…

cs.CV2023

A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking

Shaohui Mei, Jiawei Lian, Xiaofei Wang +3

Deep neural networks (DNNs) have found widespread applications in interpreting remote sensing (RS) imagery. However, it has been demonstrated in previous works that DNNs are vulner…

cs.CV20232 cited

A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings

Wenyang Liu, Yi Wang, Kejun Wu +2

File fragment classification (FFC) on small chunks of memory is essential in memory forensics and Internet security. Existing methods mainly treat file fragments as 1d byte signals…

cs.CV20225 cited

TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd Counting

Haihan Tang, Yi Wang, Lap-Pui Chau

In this paper, we propose a three-stream adaptive fusion network named TAFNet, which uses paired RGB and thermal images for crowd counting. Specifically, TAFNet is divided into one…